imgaug 0.4.0-fosscuda-2019b-Python-3.7.4This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much larger set of slightly altered images.
Accessing imgaug 0.4.0-fosscuda-2019b-Python-3.7.4
To load the module for imgaug 0.4.0-fosscuda-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load imgaug/0.4.0-fosscuda-2019b-Python-3.7.4
There is a CPU version of this module: imgaug 0.4.0-foss-2019b-Python-3.7.4
BEAR Apps Version
EL8-haswell (GPUs: NVIDIA P100)
The listed architectures consist of two part: OS-CPU.
- BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
- BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.
For more information visit the imgaug website.
This version of imgaug has a direct dependency on: fosscuda/2019b imageio/2.6.1-fosscuda-2019b-Python-3.7.4 matplotlib/3.1.1-fosscuda-2019b-Python-3.7.4 OpenCV/4.2.0-fosscuda-2019b-Python-3.7.4 Pillow/6.2.1-GCCcore-8.3.0 Python/3.7.4-GCCcore-8.3.0 scikit-image/0.16.2-fosscuda-2019b-Python-3.7.4 Shapely/1.7.0-fosscuda-2019b-Python-3.7.4
This version of imgaug is a direct dependent of: AugmentedAutoencoder/0c8100f-fosscuda-2019b-Python-3.7.4
These versions of imgaug are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
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Last modified on 19th August 2020